Analyzing mobile user data may be useful for a number of purposes. Generally, when more mobile user data is received and stored for analysis, more insight is provided as to the mobile user's activities, experiences, preferences, and the like. However, receiving and storing such large amounts of data comes at a price. Storing additional data increases power consumption, cooling requirements, noise, administrative costs, disaster and data recovery costs, backup management costs, and on and on. As such, a need exists for a system that may store enough mobile user data to gain meaningful insight to mobile user activities, experiences, preferences, and the like, while avoiding undue burden in storing the data.